Gene expression profiling and network analysis of peripheral blood monocytes in a chronic model of allergic asthma

Macrophage CD14 impacts immune defenses against influenza virus in allergic hosts

Asthma and influenza are leading causes of worldwide morbidity and mortality. Although these two conditions can co-exist in the same patient, the immune parameters that impact disease outcomes are not fully elucidated. The importance of macrophages to both conditions suggested a role for CD14, a co-receptor for endotoxin, as a regulatory mechanism for innate immune responses during asthma and influenza co-morbidity. Herein, we hypothesized that parameters of influenza morbidity will be reduced in the absence of CD14. Age and gender matched wild-type (WT) and CD14 knock-out (KO) mice were subjected to our validated model of Aspergillus-induced model of asthma and/or influenza. Characteristics of disease pathogenesis were investigated using standard methods in weight loss, flow cytometry, airway resistance, histology, quantitative real-time PCR, and viral titer quantification. The absence of CD14 did not have an impact on morbidity as these mice were equally susceptible to disease with similar airway resistance. Peribronchovascular inflammation and goblet cell content were equivalent between WT and KO mice in asthma alone and asthma and influenza co-morbidity. Co-morbid KO mice had less lymphocytes and eosinophils in the airways although their lung viral burden was equivalent to WT. Inflammatory gene signatures were altered in co-morbid mice in each genotype. CD14 expression on macrophages is necessary for airway inflammation but not for viral pathogenesis in allergic hosts.

Fluorescently activated cell sorting followed by microarray profiling of helper T cell subtypes from human peripheral blood

Background

Peripheral blood samples have been subjected to comprehensive gene expression profiling to identify biomarkers for a wide range of diseases. However, blood samples include red blood cells, white blood cells, and platelets. White blood cells comprise polymorphonuclear leukocytes, monocytes, and various types of lymphocytes. Blood is not distinguishable, irrespective of whether the expression profiles reflect alterations in (a) gene expression patterns in each cell type or (b) the proportion of cell types in blood. CD4⁺ Th cells are classified into two functionally distinct subclasses, namely Th1 and Th2 cells, on the basis of the unique characteristics of their secreted cytokines and their roles in the immune system. Th1 and Th2 cells play an important role not only in the pathogenesis of human inflammatory, allergic, and autoimmune diseases, but also in diseases that are not considered to be immune or inflammatory disorders. However, analyses of minor cellular components such as CD4⁺ cell subpopulations have not been performed, partly because of the limited number of these cells in collected samples.

Methodology/Principal Findings

We describe fluorescently activated cell sorting followed by microarray (FACS–array) technology as a useful experimental strategy for characterizing the expression profiles of specific immune cells in the circulation. We performed reproducible gene expression profiling of Th1 and Th2, respectively. Our data suggest that this procedure provides reliable information on the gene expression profiles of certain small immune cell populations. Moreover, our data suggest that GZMK, GZMH, EOMES, IGFBP3, and STOM may be novel markers for distinguishing Th1 cells from Th2 cells, whereas IL17RB and CNTNAP1 can be Th2-specific markers.

Conclusions/Significance

Our approach may help in identifying aberrations and novel therapeutic or diagnostic targets for diseases that affect Th1 or Th2 responses and elucidating the involvement of a subpopulation of immune cells in some diseases.

Differential gene expression profiles of peripheral blood mononuclear cells in childhood asthma

OBJECTIVE

Asthma is a common childhood disease with strong genetic components. This study compared whole-genome expression differences between asthmatic young children and healthy controls to identify gene signatures of childhood asthma.

METHODS

Total RNA extracted from peripheral blood mononuclear cells (PBMC) was subjected to microarray analysis. QRT-PCR was performed to verify the microarray results. Classification and functional characterization of differential genes were illustrated by hierarchical clustering and gene ontology analysis. Multiple logistic regression (MLR) analysis, receiver operating characteristic (ROC) curve analysis, and discriminate power were used to scan asthma-specific diagnostic markers.

RESULTS

For fold-change>2 and p < 0.05, there were 758 named differential genes. The results of QRT-PCR confirmed successfully the array data. Hierarchical clustering divided 29 highly possible genes into seven categories and the genes in the same cluster were likely to possess similar expression patterns or functions. Gene ontology analysis presented that differential genes primarily enriched in immune response, response to stress or stimulus, and regulation of apoptosis in biological process. MLR and ROC curve analysis revealed that the combination of ADAM33, Smad7, and LIGHT possessed excellent discriminating power.

CONCLUSIONS

The combination of ADAM33, Smad7, and LIGHT would be a reliable and useful childhood asthma model for prediction and diagnosis.